A Review of Engineering Soil Classification Systems

2009 ◽  
pp. 361-361-22 ◽  
Author(s):  
TK LIU
Keyword(s):  
Soil Classification ◽  
Classification Systems ◽  
Engineering Soil

INTERPRETATION SHEETS FOR ENGINEERING CLASSIFICATIONS IN SOIL SURVEYS

1983 ◽  
Vol 63 (4) ◽  
pp. 679-689 ◽  
Author(s):  
G. WILSON
Keyword(s):  
Key Words ◽  
Soil Classification ◽  
Classification Systems ◽  
Soil Survey ◽  
Time Element ◽  
Effective Use ◽  
Soil Surveys ◽  
Engineering Soil ◽  
Engineering Classification ◽  
Mapping Units

The UNIFIED and AASHTO systems are used in engineering to classify soils for specific purposes. To facilitate use of the soil surveys by engineers, it has been customary to interpret soil survey mapping units in terms of these engineering classification systems. The procedure, however, is often difficult to follow and normally time-consuming. When used in combination with pedotechnical setting sheets, interpretation sheets reduce this time element and provide for more effective use of the soil survey information. This paper demonstrates development and application of the interpretation sheets. Key words: Engineering soil classification, pedotechnical interpretations, UNIFIED, AASHTO, soil engineering

Computerized Cone Penetration Test for Soil Classification

2008 ◽  
Vol 2053 (1) ◽  
pp. 47-64 ◽  
Author(s):  
Murad Y. Abu-Farsakh ◽  
Zhongjie Zhang ◽  
Mehmet Tumay ◽  
Mark Morvant
Keyword(s):  
Classification System ◽  
Soil Classification ◽  
Cone Penetration Test ◽  
Classification Systems ◽  
Fuzzy Classification ◽  
Classification Methods ◽  
Penetration Test ◽  
Cone Penetration ◽  
Cone Tip Resistance ◽  
Tip Resistance

Computerized MS-Windows Visual Basic software of a cone penetration test (CPT) for soil classification was developed as part of an extensive effort to facilitate the implementation of CPT technology in many geotechnical engineering applications. Five CPT soil engineering classification systems were implemented as a handy, user-friendly, software tool for geotechnical engineers. In the probabilistic region estimation and fuzzy classification methods, a conformal transformation is first applied to determine the profile of soil classification index (U) with depth from cone tip resistance (qc) and friction ratio (Rf). A statistical correlation was established in the probabilistic region estimation method between the U index and the compositional soil type given by the Unified Soil Classification System. Conversely, the CPT fuzzy classification emphasizes the certainty of soil behavior. The Schmertmann and Douglas and Olsen methods provide soil classification charts based on cone tip resistance and friction ratio. However, Robertson et al. proposed a three-dimensional classification system that is presented in two charts: one chart uses corrected tip resistance (qt) and friction ratio (Rf); the other chart uses qt and pore pressure parameter (Bq) as input data. Five sites in Louisiana were selected for this study. For each site, CPT tests and the corresponding soil boring results were correlated. The soil classification results obtained using the five different CPT soil classification methods were compared.

A multivariate method for matching soil classification systems, with an Australian example

Soil Research ◽  
2020 ◽  
Vol 58 (6) ◽  
pp. 519
Author(s):  
H. F. Teng ◽  
R. A. Viscarra Rossel ◽  
R. Webster
Keyword(s):  
Vector Space ◽  
Classification System ◽  
Near Infrared ◽  
Soil Classification ◽  
Classification Systems ◽  
Near Infrared Reflectance ◽  
Local Systems ◽  
Soil Units ◽  
International Systems ◽  
Australian Soil

Differences between local systems of soil classification hinder the communication between pedologists from different countries. The FAO–UNESCO Soil Map of the World, as a fruit of world-wide collaboration between innumerable soil scientists, is recognised internationally. Ideally, pedologists should be able to match whole classes in their local systems to those in an international soil classification system. The Australian Soil Classification (ASC) system, created specifically for Australian soil, is widely used in Australia, and Australian pedologists wish to translate the orders they recognise into the FAO soil units when writing for readers elsewhere. We explored the feasibility of matching soil orders in the ASC to units in the FAO legend using a multivariate analysis. Twenty soil properties, variates, of 4927 profiles were estimated from their visible–near infrared reflectance (vis–NIR) spectra. We arranged the profiles in a Euclidean 20-dimensional orthogonal vector space defined by standardised variates. Class centroids were computed in that space, and the Euclidean distances between the centroids of the ASC orders and units in the FAO scheme were also computed. The shortest distance between a centroid of any ASC order and one of units in the FAO classification was treated as a best match. With only one exception the best matches were those that an experienced pedologist might expect. Second and third nearest neighbours in the vector space provided additional insight. We conclude that vis–NIR spectra represent sufficiently well the essential characters of the soil and so spectra could form the basis for the development of a universal soil classification system. In our case, we could assign with confidence the orders of the ASC to the units of the FAO scheme. A similar approach could be applied to link other national classification systems to one or other international systems of soil classification.

Classification and Mitigation of Soil Salinization

2017 ◽  
Author(s):  
Tibor Tóth
Keyword(s):  
Soil Salinity ◽  
Soil Classification ◽  
Soil Salinization ◽  
Classification Systems ◽  
Salt Accumulation ◽  
Soil Taxonomy ◽  
Sodic Soils ◽  
Water Rates ◽  
Irrigated Lands ◽  
The Right

Soil salinity has been causing problems for agriculturists for millennia, primarily in irrigated lands. The importance of salinity issues is increasing, since large areas are affected by irrigation-induced salt accumulation. A wide knowledge base has been collected to better understand the major processes of salt accumulation and choose the right method of mitigation. There are two major types of soil salinity that are distinguished because of different properties and mitigation requirements. The first is caused mostly by the large salt concentration and is called saline soil, typically corresponding to Solonchak soils. The second is caused mainly by the dominance of sodium in the soil solution or on the soil exchange complex. This latter type is called “sodic” soil, corresponding to Solonetz soils. Saline soils have homogeneous soil profiles with relatively good soil structure, and their appropriate mitigation measure is leaching. Naturally sodic soils have markedly different horizons and unfavorable physical properties, such as low permeability, swelling, plasticity when wet, and hardness when dry, and their limitation for agriculture is mitigated typically by applying gypsum. Salinity and sodicity need to be chemically quantified before deciding on the proper management strategy. The most complex management and mitigation of salinized irrigated lands involves modern engineering including calculations of irrigation water rates and reclamation materials, provisions for drainage, and drainage disposal. Mapping-oriented soil classification was developed for naturally saline and sodic soils and inherited the first soil categories introduced more than a century ago, such as Solonchak and Solonetz in most of the total of 24 soil classification systems used currently. USDA Soil Taxonomy is one exception, which uses names composed of formative elements.

scholarly journals A Comparative Analysis of a Detailed and Semi-Detailed Soil Mapping for Sustainable Land Management Using Conventional and Currently Applied Methodologies in Greece

Land ◽  
2020 ◽  
Vol 9 (5) ◽  
pp. 154 ◽  
Author(s):  
Orestis Kairis ◽  
Vassiliki Dimitriou ◽  
Chrysoula Aratzioglou ◽  
Dionisios Gasparatos ◽  
Nicholas Yassoglou ◽  
...  
Keyword(s):  
Soil Classification ◽  
Botanical Garden ◽  
Soil Mapping ◽  
Classification Systems ◽  
Soil Survey ◽  
Sustainable Land Use ◽  
Soil Taxonomy ◽  
Reference Base ◽  
World Reference Base ◽  
Soil Surveys

Two soil mapping methodologies at different scales applied in the same area were compared in order to investigate the potential of their combined use to achieve an integrated and more accurate soil description for sustainable land use management. The two methodologies represent the main types of soil mapping systems used and still applied in soil surveys in Greece. Diomedes Botanical Garden (DBG) (Athens, Greece) was used as a study area because past cartographic data of soil survey were available. The older soil survey data were obtained via the conventional methodology extensively used over time since the beginnings of soil mapping in Greece (1977). The second mapping methodology constitutes the current soil mapping system in Greece recently used for compilation of the national soil map. The obtained cartographic and soil data resulting from the application of the two methodologies were analyzed and compared using appropriate geospatial techniques. Even though the two mapping methodologies have been performed at different mapping scales, using partially different mapping symbols and different soil classification systems, the description of the soils based on the cartographic symbols of the two methodologies presented an agreement of 63.7% while the soil classification by the two taxonomic systems namely Soil Taxonomy and World Reference Base for Soil Resources had an average coincidence of 69.5%.

scholarly journals Guideline for the description of soils in the Berlin metropolitan area: an extension for surveying and mapping anthropogenic and natural soils in urban environments within the German soil classification system

2020 ◽  
Author(s):  
Mohsen Makki ◽  
Kolja Thestorf ◽  
Sabine Hilbert ◽  
Michael Thelemann ◽  
Lutz Makowsky
Keyword(s):  
Metropolitan Area ◽  
Classification System ◽  
Urban Areas ◽  
Urban Soil ◽  
Urban Soils ◽  
Soil Classification ◽  
Urban Environments ◽  
Soil Mapping ◽  
Classification Systems ◽  
Anthropogenic Soils

Abstract Purpose In urban areas, humans shape the surface, (re-)deposit natural or technogenic material, and thus become the dominant soil formation factor. The 2015 edition of the World Reference Base for Soil Resources (WRB) describes anthropogenic urban soils as Anthrosols or Technosols, but the methodological approaches and classification criteria of national soil classification systems are rather inconsistent. Stringent criteria for describing and mapping anthropogenic soils in urban areas and their application are still lacking, although more than half (53%) of the urban soils in Berlin are built-up by or contain anthropogenic material. Materials and methods On behalf of the Berlin Senate Department for the Environment, Transport and Climate Protection and in close cooperation with the German Working Group for Urban Soils, a comprehensive guideline for soil description in the Berlin metropolitan area (BMA), with special regard to anthropogenic/technogenic parent material and anthropogenic soils, has been developed. Our approach includes all previous standard works for soil description and mapping and is based on studies that have been conducted in the BMA over the last five decades. Special emphasis was placed on the integration of our manual into the classification system of the German soil mapping guideline (KA5). Results and discussion The extension of existing data fields (e.g., the further subdivision of land use types) as well as the creation of new data fields (e.g., pH value) adapted to the requirements of urban soil mapping has been carried out. Additional technogenic materials that occur in urban environments have been added to the list of anthropogenic parent materials. Furthermore, we designed appendices that clearly characterize typical soil profiles of the BMA and depict technogenic materials, their physical and chemical characteristics, as well as their origin and distribution. Our approach will set new benchmarks for soil description and mapping in urban environments, which will improve the quality of urban soil research in the BMA. It is expected that our approach will provide baselines for urban soil mapping in other metropolitan areas. Conclusions Our guideline is a comprehensive manual for the description of urban soils within a national soil classification system. This mapping guideline will be the future standard work for soil surveys and soil mapping in the federal state of Berlin. Currently, representatives from federal and state authorities are reviewing our guideline, with a view to potentially integrating key components into the classification system of the forthcoming 6th edition of the German soil mapping guideline (KA6).

Using some of Microsoft Office Excel Functions to Compute Soil Engineering Parameters Based on Raw Results of Laboratory Tests

2020 ◽  
Vol 857 ◽  
pp. 273-282
Author(s):  
Azhar Sadiq Yasun ◽  
Sultan A. Daud
Keyword(s):  
Soil Classification ◽  
Engineering Properties ◽  
Soil Parameters ◽  
Algebraic Equations ◽  
Microsoft Excel ◽  
Unconfined Compression Test ◽  
Engineering Parameters ◽  
Parameter Test ◽  
Microsoft Office ◽  
Engineering Soil

The main aim of this research can be represented as a trail to computerize the most soil engineering properties to compute them automatically using many simple Microsoft Excel functions based on raw soil test experimental data. This work will be shortening the time and effort of the geotechnical engineers calculating different soil parameters with acceptable accurate values. Nine different Microsoft Excel formulas, some of the techniques by certain Excel expressions and normal designed algebraic equations were used to present the final spreadsheet. The main computed soil parameters were (ω, LL, PL, PI, ρd,max, ωopt, k) soil classification AASHTO, (qu and cu) for unconfined compression test, (ø and c') for the direct shear test finally (Cc and Cs) for consolidation tests. To get a better understanding on how most of the programmed tools and to Microsoft Excel sheets work, the user should have knowledge about basic concepts of the certain soil parameter test and experimental steps and also the guidelines of the theory that depends to compute the parameter. Also, the user should have enough background about engineering soil properties laboratory experiments computation.

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